refactor: use Catalyner as name

.github/workflows/ci.yml

@@ -6,14 +6,14 @@ on:
       - 'master'
       - 'dev'
     paths:
-      - miko/**
+      - catalyner/**
       - tests/**
       - .github/workflows/ci.yml
       - pyproject.toml
       - poetry.lock
   pull_request:
     paths:
-      - miko/**
+      - catalyner/**
       - tests/**
       - .github/workflows/ci.yml
       - pyproject.toml
@@ -52,6 +52,6 @@ jobs:
         env:
           GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
         run: |
-          poetry run coverage run --source=./miko -m pytest -v tests/
+          poetry run coverage run --source=./catalyner -m pytest -v tests/
           poetry run coverage report
           poetry run coveralls --service=github

.github/workflows/deploy_docs.yml

@@ -7,7 +7,7 @@ on:
       - docs/**
       - README.md
       - mkdocs.yml
-      - miko/**
+      - catalyner/**
       - .github/workflows/deploy_docs.yml
 jobs:
   deploy:

README.md

@@ -1,27 +1,35 @@
-# Miko-Analyzer
+# Catlyner
 
-[![Python package](https://github.com/Cloudac7/miko-analyzer/actions/workflows/ci.yml/badge.svg)](https://github.com/Cloudac7/miko-analyzer/actions/workflows/ci.yml)
-[![Coverage Status](https://coveralls.io/repos/github/Cloudac7/miko-analyzer/badge.svg?branch=master)](https://coveralls.io/github/Cloudac7/miko-analyzer?branch=master)
+[![Python package](https://github.com/Cloudac7/catalyner/actions/workflows/ci.yml/badge.svg)](https://github.com/Cloudac7/catalyner/actions/workflows/ci.yml)
+[![Coverage Status](https://coveralls.io/repos/github/Cloudac7/catalyner/badge.svg?branch=master)](https://coveralls.io/github/Cloudac7/catalyner?branch=master)
 
-> コードで占う巫女。
-> Miko using code to perform divinition.
 
-An analysis plugin for [Deep Potential](https://github.com/deepmodeling/deepmd-kit) based chemical research.
+Machine learning aided catalysis reaction free energy calculation and post-analysis workflow, thus, analyzer for catalysis.
 
-Supporting simple calculation workflow with the help of [DPDispatcher](https://github.com/deepmodeling/dpdispatcher).
+Mainly developed on MacOS Catalina.
+
+> Former Miko-Analyzer
 
 ## Installation
 
 To install, clone the repository:
 
 ```
-git clone https://github.com/cloudac7/miko-analyzer.git
+git clone https://github.com/cloudac7/catalyner.git
 ```
 
 and then install with `pip`:
 
 ```
-cd miko-analyzer
+cd catalyner
 pip install .
 ```
 
+## Acknowledgement
+This project is inspired by and built upon the following projects:
+- [ai2-kit](https://github.com/chenggroup/ai2-kit): A toolkit featured artificial intelligence × ab initio for computational chemistry research.
+- [DP-GEN](https://github.com/deepmodeling/dpgen): A concurrent learning platform for the generation of reliable deep learning based potential energy models.
+- [ASE](https://wiki.fysik.dtu.dk/ase/): Atomic Simulation Environment.
+- [DPDispatcher](https://github.com/deepmodeling/dpdispatcher): Generate and submit HPC jobs.
+- [Metadynminer](https://github.com/spiwokv/metadynminer): Reading, analysis and visualization of metadynamics HILLS files produced by Plumed. As well as its Python implementation [Metadynminer.py](https://github.com/Jan8be/metadynminer.py).
+- [stringmethod](https://github.com/apallath/stringmethod): Python implementation of the string method to compute the minimum energy path.

miko/__main__.py → catalyner/__main__.py

@@ -1,5 +1,5 @@
 import sys
 
 if __name__ == '__main__':
-    from miko.cmdline.base import cli
+    from catalyner.cmdline.base import cli
     sys.exit(cli())

catalyner/cmdline/base.py

@@ -0,0 +1,14 @@
+import click
+import logging
+from importlib.metadata import entry_points
+
+
+entries = entry_points().get('catalyner.cmdline', [])
+if entries != []:
+    entries_cli = [i.load() for i in entries]
+else:
+    entries_cli =[]
+
+cli = click.CommandCollection(sources=[
+    *entries_cli
+])

miko/metad/fes.py → catalyner/metad/fes.py

@@ -9,9 +9,9 @@
 from numpy.typing import ArrayLike
 from matplotlib.colors import Colormap
 
-from miko.metad.hills import Hills
-from miko.graph.plotting import canvas_style
-from miko.utils.log_factory import logger
+from catalyner.metad.hills import Hills
+from catalyner.graph.plotting import canvas_style
+from catalyner.utils.log_factory import logger
 
 
 class FreeEnergySurface:
@@ -20,7 +20,7 @@ class FreeEnergySurface:
 
     Usage:
     ```python
-    from miko.metad.fes import FreeEnergySurface
+    from catalyner.metad.fes import FreeEnergySurface
     fes = FreeEnergySurface(hills)
     ```
 

miko/metad/profile.py → catalyner/metad/profile.py

@@ -5,9 +5,9 @@
 from typing import List, Optional, Union
 from matplotlib.colors import Colormap
 
-from miko.graph.plotting import canvas_style
-from miko.metad.fes import FreeEnergySurface
-from miko.metad.hills import Hills
+from catalyner.graph.plotting import canvas_style
+from catalyner.metad.fes import FreeEnergySurface
+from catalyner.metad.hills import Hills
 
 
 class FreeEnergyProfile:

miko/metad/string.py → catalyner/metad/string.py

@@ -15,8 +15,8 @@
 from scipy.interpolate import Rbf, griddata, interp1d, RegularGridInterpolator
 from typing import Literal, List, Union, Tuple, Optional
 
-from miko.utils import logger
-from miko.metad.fes import FreeEnergySurface
+from catalyner.utils import logger
+from catalyner.metad.fes import FreeEnergySurface
 
 
 class StringMethod:

miko/structure/cluster.py → catalyner/structure/cluster.py

@@ -8,7 +8,7 @@
 from MDAnalysis import Universe
 
 
-from miko.structure.lindemann_index import LindemannIndex
+from catalyner.structure.lindemann_index import LindemannIndex
 
 
 class Cluster(object):

miko/structure/dynamic_selection.py → catalyner/structure/dynamic_selection.py

@@ -108,7 +108,7 @@ class AxisMaxDistance(AnalysisBase):
 
     Examples:
         >>> import MDAnalysis as mda
-        >>> from miko.structure.dynamic_selection import AxisMaxDistance
+        >>> from catalyner.structure.dynamic_selection import AxisMaxDistance
         >>> u = mda.Universe("system.gro", "system.trr")
         >>> ag1 = u.select_atoms("protein")
         >>> ag2 = u.select_atoms("resname LIG")

miko/tesla/ai2_kit/exploration.py → catalyner/tesla/ai2_kit/exploration.py

@@ -4,10 +4,10 @@
 
 import numpy as np
 
-from miko.utils.log_factory import logger
-from miko.utils.lammps import lammps_variable_parser
-from miko.tesla.base.exploration import ExplorationAnalyzer
-from miko.tesla.ai2_kit.task import CllAnalyzer
+from catalyner.utils.log_factory import logger
+from catalyner.utils.lammps import lammps_variable_parser
+from catalyner.tesla.base.exploration import ExplorationAnalyzer
+from catalyner.tesla.ai2_kit.task import CllAnalyzer
 
 
 def read_model_deviation(model_devi_path: Path):

miko/tesla/ai2_kit/labeling.py → catalyner/tesla/ai2_kit/labeling.py

@@ -1,8 +1,8 @@
 import re
 
-from miko.tesla.base.labeling import LabelingAnalyzer
-from miko.tesla.ai2_kit.task import CllAnalyzer
-from miko.graph.plotting import canvas_style
+from catalyner.tesla.base.labeling import LabelingAnalyzer
+from catalyner.tesla.ai2_kit.task import CllAnalyzer
+from catalyner.graph.plotting import canvas_style
 
 
 class CllLabelingAnalyzer(LabelingAnalyzer, CllAnalyzer):

miko/tesla/ai2_kit/task.py → catalyner/tesla/ai2_kit/task.py

@@ -8,7 +8,7 @@
 from ai2_kit.core.checkpoint import set_checkpoint_file
 from ai2_kit.workflow.cll_mlp import CllWorkflowConfig
 
-from miko.tesla.base.task import BaseTask, BaseAnalyzer
+from catalyner.tesla.base.task import BaseTask, BaseAnalyzer
 
 
 class CllTask(BaseTask):

miko/tesla/ai2_kit/training.py → catalyner/tesla/ai2_kit/training.py

@@ -3,10 +3,10 @@
 import numpy as np
 from matplotlib import pyplot as plt
 
-from miko.utils import logger
-from miko.graph.plotting import canvas_style
-from miko.tesla.base.training import TrainingAnalyzer
-from miko.tesla.ai2_kit.task import CllAnalyzer, CllTask
+from catalyner.utils import logger
+from catalyner.graph.plotting import canvas_style
+from catalyner.tesla.base.training import TrainingAnalyzer
+from catalyner.tesla.ai2_kit.task import CllAnalyzer, CllTask
 
 
 class CllTrainingAnalyzer(TrainingAnalyzer, CllAnalyzer):

miko/tesla/base/exploration.py → catalyner/tesla/base/exploration.py

@@ -11,9 +11,9 @@
 import seaborn as sns
 from matplotlib import pyplot as plt
 
-from miko.utils.log_factory import logger
-from miko.graph.plotting import canvas_style, square_grid
-from miko.tesla.base.task import BaseAnalyzer
+from catalyner.utils.log_factory import logger
+from catalyner.graph.plotting import canvas_style, square_grid
+from catalyner.tesla.base.task import BaseAnalyzer
 
 
 def read_model_deviation(model_devi_path: Path):
@@ -251,7 +251,7 @@ def plot_single_iteration(
             kwargs (_type_, optional): Additional keyword arguments. Include other params, such as:
                 `temps`: please use the value of `group_by`, whose default input is `"temps"`.
                 `label_unit`: the unit of `select_value`, such as 'Å'.
-                Parameters of `canvas_style`: please refer to `miko.graph.plotting.canvas_style`.
+                Parameters of `canvas_style`: please refer to `catalyner.graph.plotting.canvas_style`.
 
         Returns:
             Figure: A plot for different desired values.

miko/tesla/base/labeling.py → catalyner/tesla/base/labeling.py

@@ -7,10 +7,10 @@
 from ase.io import read
 from matplotlib import pyplot as plt
 
-from miko.utils.log_factory import logger
-from miko.utils.log_factory import LogFactory
-from miko.tesla.base.task import BaseTask, BaseAnalyzer
-from miko.graph.plotting import canvas_style
+from catalyner.utils.log_factory import logger
+from catalyner.utils.log_factory import LogFactory
+from catalyner.tesla.base.task import BaseTask, BaseAnalyzer
+from catalyner.graph.plotting import canvas_style
 
 
 

miko/tesla/base/training.py → catalyner/tesla/base/training.py

@@ -3,9 +3,9 @@
 import numpy as np
 from matplotlib import pyplot as plt
 
-from miko.utils import logger
-from miko.graph.plotting import canvas_style
-from miko.tesla.base.task import BaseAnalyzer, BaseTask
+from catalyner.utils import logger
+from catalyner.graph.plotting import canvas_style
+from catalyner.tesla.base.task import BaseAnalyzer, BaseTask
 
 
 class TrainingAnalyzer(BaseAnalyzer):

miko/tesla/dpgen/exploration.py → catalyner/tesla/dpgen/exploration.py

@@ -8,10 +8,10 @@
 import numpy as np
 from matplotlib import pyplot as plt
 
-from miko.utils.log_factory import logger
-from miko.graph.plotting import canvas_style, square_grid
-from miko.tesla.base.exploration import ExplorationAnalyzer, PlottingExploartion
-from miko.tesla.dpgen.task import DPAnalyzer
+from catalyner.utils.log_factory import logger
+from catalyner.graph.plotting import canvas_style, square_grid
+from catalyner.tesla.base.exploration import ExplorationAnalyzer, PlottingExploartion
+from catalyner.tesla.dpgen.task import DPAnalyzer
 
 
 class DPExplorationAnalyzer(ExplorationAnalyzer, DPAnalyzer):
@@ -95,7 +95,7 @@ def plot_single_iteration(
             kwargs (_type_, optional): Additional keyword arguments. Include other params, such as:
                 `temps`: please use the value of `group_by`, whose default input is `"temps"`.
                 `label_unit`: the unit of `select_value`, such as 'Å'.
-                Parameters of `canvas_style`: please refer to `miko.graph.plotting.canvas_style`.
+                Parameters of `canvas_style`: please refer to `catalyner.graph.plotting.canvas_style`.
 
         Returns:
             Figure: A plot for different desired values.

miko/tesla/dpgen/labeling.py → catalyner/tesla/dpgen/labeling.py

@@ -1,7 +1,7 @@
 from typing import Optional
 
-from miko.tesla.base.labeling import LabelingAnalyzer
-from miko.tesla.dpgen.task import DPTask, DPAnalyzer
+from catalyner.tesla.base.labeling import LabelingAnalyzer
+from catalyner.tesla.dpgen.task import DPTask, DPAnalyzer
 
 
 class DPLabelingAnalyzer(LabelingAnalyzer, DPAnalyzer):

miko/tesla/dpgen/task.py → catalyner/tesla/dpgen/task.py

@@ -2,7 +2,7 @@
 from pathlib import Path
 from typing import Optional
 
-from miko.tesla.base.task import BaseTask, BaseAnalyzer
+from catalyner.tesla.base.task import BaseTask, BaseAnalyzer
 
 
 class DPTask(BaseTask):

miko/tesla/dpgen/training.py → catalyner/tesla/dpgen/training.py

@@ -4,10 +4,10 @@
 import numpy as np
 from matplotlib import pyplot as plt
 
-from miko.utils import logger
-from miko.graph.plotting import canvas_style
-from miko.tesla.base.training import TrainingAnalyzer
-from miko.tesla.dpgen.task import DPAnalyzer
+from catalyner.utils import logger
+from catalyner.graph.plotting import canvas_style
+from catalyner.tesla.base.training import TrainingAnalyzer
+from catalyner.tesla.dpgen.task import DPAnalyzer
 
 class DPTrainingAnalyzer(TrainingAnalyzer, DPAnalyzer):
     """Analyzer for training tasks.

miko/utils/log_factory.py → catalyner/utils/log_factory.py

@@ -6,7 +6,7 @@ class LogFactory(object):
     """
     For logging
     """
-    def __init__(self, logger=None, log_dir=None, log_name="miko.log"):
+    def __init__(self, logger=None, log_dir=None, log_name="catalyner.log"):
         self.log_path = Path.cwd() if log_dir is None else Path(log_dir)
         self.logger = logging.getLogger(logger)
         self.logger.setLevel(logging.DEBUG)

docs/Usage/cluster_structures.md

@@ -6,7 +6,7 @@
 其他的参数请以可选参数形式传入。
 
 ```python
-from miko.structure.cluster import Cluster
+from catalyner.structure.cluster import Cluster
 
 trajfile = "./dump.lammpstrj"
 c = Cluster(trajfile, topology_format="LAMMPSDUMP", dt=0.0005)

docs/Usage/dpgen_analysis.md

@@ -5,7 +5,7 @@
 首先，导入环境：
 
 ```python
-from miko.tesla.dpgen import DPTask
+from catalyner.tesla.dpgen import DPTask
 ```
 
 加载DP-GEN工作目录：
@@ -26,7 +26,7 @@ t = DPTask(
 导入分析器（`DPAnalyzer`），这里我们选择训练，即：
 
 ```python
-from miko.tesla.dpgen.training import DPTrainingAnalyzer
+from catalyner.tesla.dpgen.training import DPTrainingAnalyzer
 ```
 
 从任务初始化分析器实例：
@@ -51,7 +51,7 @@ fig.set_size_inches((12,12))
 类似地，我们也可以对模型的model deviation分布进行分析：
 
 ```python
-from miko.tesla.dpgen.exploration import DPExplorationAnalyzer
+from catalyner.tesla.dpgen.exploration import DPExplorationAnalyzer
 ana = DPExplorationAnalyzer(t)
 ```